R.V. work was supported by a Roche Postdoctoral Fellowship (2014-2017).

Ethical approval for this study was provided by the Federal Food Safety and Veterinary Office of Switzerland. All animal experiments were conducted in strict adherence to the Swiss federal ordinance on animal protection and welfare as well as according to the rules of the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC).
1. Generation of Brain Free-floating Sections
<ol>
	<li>To ensure optimal sample quality, prepare a fresh solution of 2% paraformaldehyde (PFA) in phosphate buffer saline (PBS) on the day of the perfusion. 
	CAUTION: PFA is moderately toxic by skin contact and a probable carcinogen. Use nitrile gloves to handle PFA and prepare the solution under a chemical fume hood.
	<ol>
		<li>Prepare 60 mL of PFA solution per animal.</li>
		<li>Bring PFA into solution by increasing the pH with 180 - 200 &#181;L of a 5 M KOH solution for every 100 mL of PBS and heating the solution up to 60 &#176;C. 
		NOTE: NaOH should not be used as it negatively impacts tissue preservation upon fixation.</li>
		<li>Let the solution cool down to room temperature and bring the pH down to 7.4 using HCl. Filter the solution using filter paper (see Table of Materials).</li>
	</ol>
	</li>
	<li>Perform a whole mouse fixation via transcardial perfusion as previously described15 with some modifications. First, flush the blood from the vasculature using 20 mL of PBS then perfuse with 40 mL of 2% PFA.</li>
	<li>Remove the brain from the skull as previously described15.</li>
	<li>Immerse a freshly 2% PFA-perfused&#160;brain in 20 mL of 2% PFA for 7 h at 4 &#176;C for post-fixation. 
	NOTE: Increasing the incubation in PFA is not recommended as it can prevent detection of intracellular structures.</li>
	<li>Extensively wash the brain with ice-cold PBS.</li>
	<li>Embed fixed brains in agarose.
	<ol>
		<li>Prepare a 3% agarose solution in PBS using a microwave for heating. Gently swirl the solution to cool it down but avoid solidification.</li>
		<li>Dry off the excess of PBS around the brain before immersion into the agarose solution in a plastic container. Rotate the brain inside the agarose to remove air bubbles. Allow the agarose to solidify by cooling it down on ice.</li>
		<li>Carefully remove the agarose block from the plastic container and cut a cube around the brain using a razor blade.Mount the brain onto a vibratome specimen holder (see Table of Materials) using cyanoacrylate glue (see Table of Materials). Allow sufficient time for the glue to solidify before proceeding with the sectioning.</li>
	</ol>
	</li>
	<li>Transfer the brain in the specimen holder to the vibratome buffer tray filled with PBS.Use the vibratome to section 100 &#181;m brain slices (sagittal or coronal).Collect brain sections in a 6-well plate previously filled with PBS.</li>
	<li>Upon finishing brain sectioning, carefully remove PBS and replace with a 1:1 solution of PBS/glycerol.</li>
	<li>Store sections in PBS/glycerol at -20 &#176;C.</li>
</ol>
2. Cell or Organelle Labelling by Immunofluorescence Staining
<ol>
	<li>Carefully transfer a brain section into a well of a 24-well plate previously filled with 500 &#181;L of PBS per well. The section will remain in the same well until the end of the procedure.</li>
	<li>Rinse the section twice with 500 &#181;L of PBS for 5 min under gentle agitation.</li>
	<li>Remove the PBS and perform simultaneous blocking and permeabilization of brain slices.
	<ol>
		<li>Prepare a blocking and permeabilization solution with 0.3% Triton-X and 10% donkey serum in PBS. 
		NOTE: Donkey serum can be replaced with goat serum to match the host species of the specific secondary antibodies used.</li>
		<li>Incubate sections with 250 &#181;L of blocking and permeabilization solution for 1 h at room temperature under gentle agitation.</li>
	</ol>
	</li>
	<li>Remove the solution and add a PBS solution containing 5% donkey serum and the primary antibody at an appropriate dilution (e.g., 1:100 to 1:1,000). Incubate overnight at 4 &#176;C under gentle agitation. 
	NOTE: See the Table of Materials for a list of antibodies that successfully label the different cell types of the NVU with this protocol. The optimal dilution of primary antibodies must be determined empirically. For simultaneous labelling of different antigens, dilute all primary antibodies in the same solution. All primary antibodies must be raised in different species. To improve antibody penetration, samples can be incubated for up to 72 h at 4 &#176;C.</li>
	<li>Remove antibody solution and wash sections three times for 10 min in PBS under gentle agitation at room temperature. Remove PBS and add 250 &#181;L PBS solution containing 5% donkey serum and the appropriate species-specific fluorescently labelled secondary antibody. Incubate sections at room temperature for 1 h under gentle agitation.
	<ol>
		<li>See Table of Materials for a list of the secondary antibodies used with this protocol.</li>
	</ol>
	</li>
	<li>Remove the antibody solution and wash sections three times for 10 min in PBS under gentle agitation at room temperature.</li>
	<li>Remove PBS and add 250 &#181;L of a 4&#39;,6-diamidino-2-phenylindole (DAPI) solution with&#160;a final concentration of 1 &#181;g/mL. Incubate sections at room temperature for 10 minutes under gentle agitation. Remove DAPI solution and wash sections 3 times for 5 min with PBS.</li>
	<li>Mount the brain section on bonding microscopy slides (e.g., histo-bond glass slides).Carefully remove excess PBS around the section on the slide. Add a drop of mounting medium (see Table of Materials) on top of the brain section and carefully cover it with a 0.17 mm (No. 1.5) borosilicate glass coverslip.
	<ol>
		<li>Store samples at 4 &#176;C protected from light until performing the image acquisition.</li>
	</ol>
	</li>
</ol>
3. High-resolution Confocal Imaging of the Blood-brain Barrier
<ol>
	<li>Perform image acquisition with a suitable laser-scanning confocal microscope (see Table of Materials) with laser lines at 405, 488, 561, and 633 nm for excitation of fluorophores in the blue, green, orange, and red regions of the light spectrum. For image acquisition, use a 63X oil objective with a numerical aperture of 1.4.</li>
	<li>In the acquisition menu of the software that controls the microscope, set the image acquisition parameters. In the drop-down menu of &#8216;Image size&#8217;, select a value of 1024 x 1024 pixels. Modify the pixel size to a value between 200 and 300 nm by adjusting the value of the &#8216;Zoom&#8217; menu.&#8221; 
	NOTE: For the analysis of intracellular structures, reduce the pixel size to 75 nm. This image size setting substantially increases the acquisition time and can be reduced to 512 x 512 pixels to decrease the acquisition time by imaging a smaller field of view.</li>
	<li>In the &#39;Acquisition Speed&#39; drop-down menu, select a value of 400 Hz, i.e. 400 lines per second. In the &#39;systems settings&#39; menu, select the &#39;Pixel depth&#39; drop down menu, and change the value to 12 bit.</li>
	<li>In the microscope software, within the &#39;acquisition&#39; tab, toggle on the option for sequential frame acquisition. Set the optical section thickness to a value between 0.75 and 1 &#181;m for each channel by modifying the value in the &#39;Pinhole&#39; menu.</li>
	<li>In the panel for fluorescent excitation, activate the laser required to optimally excite the fluorophores in the sample, for example a 488 nm laser line for a green-emitting fluorophore. 
	NOTE: Use a fluorophore spectra viewer (see Table of Materials) to select the adequate excitation laser.</li>
	<li>In the panel for fluorescent detection, move the slider to select the wavelengths that will be measured in each channel, for example between 510 and 550 nm for a green-emitting fluorophore. 
	NOTE: Use a fluorophore spectra viewer (see Table of Materials) to select the adequate detection wavelengths.</li>
	<li>Add a drop of immersion oil with a refractive index of 1.52 on top of the coverslip with the brain section to match the refractive index of the glass coverslip and objective. Place the sample in the microscope and turn on the epifluorescent lamp to visualize the sample using the microscope binoculars.</li>
	<li>Using the buttons on the microscope stand, change the filter wheel to select a filter appropriate for visualizing DAPI-stained nuclei. Use the coarse focus to bring the signal from DAPI-stained nuclei into focus.</li>
	<li>Using the buttons on the microscope stand, change filters to visualize the signal from vascular markers (for example, CollagenIV or CD31) and center the field of view on an individual capillary segment.</li>
	<li>Press the button to start the live-scan mode. During scanning adjust the gain and laser intensity for each channel to maximize the dynamic range of the images and avoid pixel saturation. 
	NOTE: Use a look-up table which labels saturated pixels to visually assess over-saturation. To avoid signal over-saturation, adjust the settings with the sample which is expected to have the highest fluorescent signal.</li>
	<li>Set the value for line averaging to 2. 
	NOTE: When using higher acquisition speeds, increase this value to reduce noise.</li>
	<li>Establish begin and end sections for performing optical z-stacks that span the whole volume of the capillary. Use a step size of 0.45 &#181;m. 
	NOTE: If images will be used for subsequent quantification, keep the same acquisition settings for the complete data set.</li>
	<li>For quantification, acquire 10 to 20 z-stacks per section from at least three different mice for statistical comparisons. 
	NOTE: Acquire the full data set in the same session to reduce the variability arising from sample bleaching and laser intensity fluctuations.</li>
</ol>
4. Image Processing and 3D Reconstruction of the Neurovascular Unit
<ol>
	<li>(Optional) To increase the axial resolution of the acquired z-stacks, perform deconvolution of the image data set using appropriate software (see Table of Materials).
	<ol>
		<li>In the deconvolution software, change the settings to perform &#34;Blind&#34; deconvolution, (i.e., using an adaptive point-spread function).</li>
		<li>In the deconvolution software settings, toggle on the option for Background removal; this option will determine the smallest intensity value in the image stack and subtract it from the intensity values from all pixels in the image.</li>
		<li>In the deconvolution software settings, toggle off the options for rescaling intensity and resizing to 16 bit depth; these options will keep the original intensity values and dynamic range of the images.</li>
		<li>In the menu of &#39;Refractive index&#39;, set the value to 1.52. In the &#39;Set Wavelength&#39; menu, select the emission values for each image channel. For example, select 520 for a green-emitting fluorophore.</li>
	</ol>
	</li>
	<li>Open the image data set using software suitable for visualization and analysis of 3-dimensional data sets (see Table of Materials). In the image analysis software, press the &#34;Surpass&#34; button to render the 3D volume of capillaries.</li>
	<li>In the image analysis software press the &#34;Add new surface&#34; button to segment the capillary surface. Use the bottom arrows to move between steps in the surface creation wizard.
	<ol>
		<li>In the &#39;Create&#39; tab, set the source channel to the channel with capillary marker, for example CollagenIV, and set the surface area detail to a value of 0.5 &#181;m. 
		NOTE: The latter option applies a Gaussian filter to the image and determines the smoothness of the surface.</li>
		<li>In the &#39;create&#39; tab, toggle on the option for absolute intensity threshold. 
		NOTE: This option will create a surface by generating a mask based on the absolute intensity of the selected channel in the image.</li>
		<li>On the next step in the surface creation wizard, adjust the lower intensity threshold for the surface by moving the sliding window across the intensity histogram until the rendered mask covers the whole capillary in the image. Determine the value range for this parameter empirically for each data set.</li>
		<li>On the final step of the surface creation wizard, click on the drop-down menu under &#34;Filter Type&#34; and select the option &#39;Number of Voxels&#39;. Set the minimum number of voxels to a value between 1.0e5 to 2.0e5. 
		NOTE: This option will exclude surfaces with a small number of voxels, for example, small segments of capillaries at the edge of the frame.</li>
		<li>Finish the surface creation wizard and save the creation parameters by clicking &#34;Remember parameters&#34; in the rebuild tab of the surface menu.</li>
		<li>Repeat the procedure for the whole imaging data set by loading the parameter set used for the first image. Adjust the parameters for the intensity, threshold, and minimum number of voxels for each image to account for differences in background intensity and capillary morphology, respectively.</li>
	</ol>
	</li>
	<li>To segment intracellular vesicular structures (e.g., immunoglobulin-filled endosomes), first create a new channel that only includes fluorescent signal from within the capillary. 
	NOTE: This process will define a region of interest by creating a mask using the capillary surface created in step 4.3
	<ol>
		<li>Select the &#39;edit&#39; menu in the &#39;capillary surface&#39; panel. Under &#39;mask properties&#39;, click &#34;Mask All&#34;. Select the channel that contains the intracellular vesicle signal as the &#39;Source Channel&#39; and toggle on the option &#34;Duplicate channel before applying mask&#34;.</li>
		<li>In the &#39;mask settings&#39; column, select &#34;Constant inside/outside&#34; and &#34;Set voxels outside surface to:&#34; and set its value to 0.00. 
		NOTE: This process will create an additional channel in the image where all voxels outside the capillary mask will have an intensity value of 0. To quantify events outside of the capillary (i.e., in the brain parenchyma), choose &#34;Set voxels inside surface to:&#34; and set its value to 0.00.</li>
		<li>To segment vesicular structures, press the button to start the &#34;Add new Spots&#34; wizard. Use the bottom arrows to move between steps in the surface creation wizard.</li>
		<li>In the create tab, use the drop down menu under &#34;Source Channel&#34; to select the intracellular masked channel created in step 4.4.4.</li>
		<li>In the create tab, under the &#34;Spot detection&#34; section, set the estimated XY diameter to a value between 0.5 and 1 &#181;m, depending on the average size of vesicles observed in the experiment. This option determines the smallest size which will be detected by the segmentation algorithm.</li>
		<li>In the create tab, under the &#34;Spot detection&#34; section, toggle on the option for &#34;Background Subtraction&#34;. 
		NOTE: This option will smooth the image with a Gaussian filter of 0.75 spot radius (from the value selected in step 4.4.7) and then subtracting the intensity of the original image Gaussian filtered by 0.88 spot radius.</li>
		<li>In the &#39;create&#39; tab, press the dropdown menu under &#39;Filter Type&#39; and select &#34;Quality&#34;. Note that this will segment the image by applying thresholds based on the intensity at the center of the spots. Adjust the lower intensity threshold by moving the sliding window across the &#39;Quality&#39; histogram until the majority of identifiable vesicles are labelled. 
		NOTE: The value range for this parameter needs to be determined empirically for each data set.</li>
		<li>Finish the spot creation wizard and save the creation parameters by pressing the button &#34;Remember parameters&#34; in the rebuild tab of the surface menu.</li>
		<li>Repeat the procedure for the whole imaging data set by loading the parameter set used for the first image. Adjust the parameters for the &#39;Quality intensity threshold&#39; for each image to account for differences in background intensity.</li>
	</ol>
	</li>
</ol>
5. Quantification of Intracellular Transport at the BBB
<ol>
	<li>Quantify the volume (in &#181;m3) and area (in &#181;m2) of the capillary segment. In the analysis software, access the statistics panel of the vascular surface created in step 4.3. Select the &#39;Detailed&#39; tab, and use the drop down menu to select &#34;All values&#34; to find the values for volume and area.</li>
	<li>Quantify the number of vesicles within the capillary segment. In the analysis software, access the statistics panel of the spots created in step 4.4. Select the &#39;Overall&#39; tab to find the value of the total number of spots in the image.</li>
	<li>To calculate the number of vesicles per capillary volume, for each image normalize the number of spots by the volume calculated in step 5.1. Multiply this value by 1,000 to get the number of vesicles per 1,000 &#181;m3 of the capillary volume.</li>
	<li>To quantify the total intensity within the capillary create a new surface that covers the entire image following the instructions described in steps 4.3 with the following modifications. Select the channel that contains the pertinent signal (e.g., mIgG) as source channel and set the value of the surface area detail level to 5 &#181;m. To create a surface that covers the whole image, set the value of the lower intensity threshold to 0.</li>
	<li>In the analysis software, access the statistics panel of the surface created in step 5.4. Select the &#34;Detailed&#34; tab, and use the drop down menu to select &#34;All values&#34;. Record the values for &#39;Intensity Sum&#39; for the channels of interest; this parameter corresponds to the sum of individual intensity values over all pixels. 
	NOTE: For an intracellular signal, this corresponds to the duplicated channel with voxels outside surface set to 0.0. For a signal in the brain parenchyma, this corresponds to the duplicated channel with voxels inside surface set to 0.0.</li>
	<li>To calculate the fluorescence intensity per capillary volume, for each image normalize the intensity by the volume calculated in step 5.1. Multiply this value by 1,000 to get the fluorescence intensity value per 1,000 &#181;m3 of the capillary volume. 
	NOTE: For fluorescent signals in the brain parenchyma, normalize the values by the total image volume minus the capillary volume and multiply by 1,000 to get the total intensity per 1,000 &#181;m3 of brain parenchyma.</li>
	<li>Repeat the procedure for the whole data set and use appropriate software to perform statistical analysis of the data.</li>
</ol>

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A., Barres, B. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pericytes+are+required+for+blood-brain+barrier+integrity+during+embryogenesis.">Pericytes are required for blood-brain barrier integrity during embryogenesis.</a> Nature. 468 (7323), 562-566 (2010).</li><li>Bell, R. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pericytes+control+key+neurovascular+functions+and+neuronal+phenotype+in+the+adult+brain+and+during+brain+aging.">Pericytes control key neurovascular functions and neuronal phenotype in the adult brain and during brain aging.</a> Neuron. 68 (3), 409-427 (2010).</li><li>Ben-Zvi, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mfsd2a+is+critical+for+the+formation+and+function+of+the+blood-brain+barrier.">Mfsd2a is critical for the formation and function of the blood-brain barrier.</a> Nature. 509 (7501), 507-511 (2014).</li><li>Stewart, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Endothelial+vesicles+in+the+blood-brain+barrier:+are+they+related+to+permeability.">Endothelial vesicles in the blood-brain barrier: are they related to permeability.</a> Cell Mol Neurobiol. 20 (2), 149-163 (2000).</li><li>Follain, G., Mercier, L., Osmani, N., Harlepp, S., Goetz, J. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Seeing+is+believing+-+multi-scale+spatio-temporal+imaging+towards+in+vivo+cell+biology.">Seeing is believing - multi-scale spatio-temporal imaging towards in vivo cell biology.</a> J Cell Sci. 130 (1), 23-38 (2017).</li></ol>

Authors are under paid employment by Roche.

The protocol outlined above describes the preparation of brain free-floating sections, immunofluorescent staining, image acquisition, and analysis parameters for high-resolution microscopy of the BBB. This method has been recently used to investigate the localization of antibody delivery platforms3, the transport of endogenous IgG across the BBB17, and the heterogeneity of the BBB upon pericyte loss18. Different steps in the protocol can be modified to adapt to the specific goal of the experiment. First, the use of thick (100 &#181;m) sections facilitates their handling during the immunostaining and mounting procedures. It also allows for 3D reconstruction of the capillary network, the neurovascular unit, and for the generation of capillary and NVU cross-sections. However, penetration of antibodies within the tissue sections may vary and some antibody staining can be restricted to the superficial layer of the tissue close to the coverslip. The protocol can be modified by increasing the concentration of detergent during the permeabilization step and/or the length of the permeabilization step to improve antibody penetration into the tissue. Second, image quality may be compromised when attempting to acquire images deeper within the tissue (usually 20 to 30 &#181;m below the surface) due to light scattering as well as optical aberrations from refractive index mismatch. To overcome this problem, new methods for tissue clearing and active antibody penetration20 can be combined with this protocol to image larger volumes of tissue. Third, deconvolution is performed after image acquisition to improve the axial resolution of the image. The choice of the blind deconvolution algorithm used in this protocol was based on (i) its ease of use, as no pre-calculation of the point-spread function is required, (ii) its robustness for improving image quality21, and (iii) the lack of artefacts on mIgG intracellular structures after implementation. Depending on the intracellular structures visualized in the sample, other deconvolution algorithms may result in higher image quality. The following references21,22 provide an extensive discussion on the advantages and limitations of additional algorithms for image deconvolution. Finally, the use of an image analysis software package allowed the segmentation of capillaries and intracellular structures in three dimensions. Clearly image analysis is not restricted to the software described in the protocol and alternative packages, for example those discussed in reference23, can be used to segment images. The suitability of different software programs for the analysis of intracellular structures across the BBB should be verified empirically by assessing the accuracy of image segmentation.
Since this method is based on fixed samples, it does not provide direct information about the dynamics of transcytosis across the BBB. However, it can be combined with time-course experiments24, for example by intravenously injecting the molecule of interest and measuring its accumulation within BECs at different time points after injection, to reconstruct the kinetics of intracellular transport. The advantage of this approach is that it allows for the analysis of deep brain regions, as shown in18, which are currently inaccessible to intravital live imaging approaches. A critical step during the protocol is the careful monitoring of tissue fixation. Fixation with 4% PFA dramatically reduces the immunogenicity of intracellular organelles and of endogenous or peripherally administered immunoglobulins17 (Figure 1B). A limitation of this protocol is its requirement of high-quality antibodies (i.e., low non-specific staining, low cross-reactivity) suitable for immunofluorescence. Provided that such reagents are available, the method can be applied to investigate the intracellular localization of any protein of interest. For example, the protocol was used to identify lysosomes in brain endothelial cells17. It should also be noted that since this protocol is based on confocal microscopy, the lateral resolution is limited by diffraction and cannot resolve structures smaller than approximately 175 to 250 nm (Figure 2).
Previous studies have performed detailed analysis of the cellular composition of the neurovascular unit using confocal microscopy25,26. However, investigating intracellular transport at the BBB relies mostly on the use of transmission electron microscopy19,27,28. While this method offers the highest lateral resolution of intracellular structures, electron microscopy remains a challenging technique with low throughput. Moreover, the number of different molecular targets which can be visualized by EM is very limited. This protocol offers an accessible alternative to investigate intracellular transport at the BBB. The complete procedure, from brain collection to image analysis, can be performed in 5 to 6 days. If suitable antibodies are available, immunofluorescence allows simultaneous detection of multiple cell types/molecules within the same sample. Moreover this protocol could be combined with super-resolution microscopy techniques to overcome the limitations in spatial resolution29. Overall, the protocol described above enables the quantification of changes in the intracellular localization of proteins of interest within the neurovascular unit. Its application for different genetic or pharmacological perturbations will allow investigating the intracellular structure and transport functions of the BBB in vivo.

The blood-brain barrier (BBB) is a continuous cellular barrier formed by astrocytes, pericytes, neurons, and endothelial cells that separates the central nervous system (CNS) from the blood circulation1. The regulation of transport across the BBB plays a crucial role in maintaining brain homeostasis and is mediated by specialized properties of brain endothelial cells (BECs). The presence of tight intercellular junctions between BECs and a low basal rate of transcytosis limit the paracellular and transcellular transport of blood-borne molecules, respectively2. Recently, the transcytosis pathway in BECs has been harnessed to enhance delivery of therapeutic large molecules to the brain3,4. However, the mechanisms of transcytosis across the BBB have not yet been fully characterized5,6.
Extensive work has been done in vitro to decipher the cellular and molecular mechanisms regulating intracellular transport across BECs7,8,9,10,11, but such systems fail to recapitulate the complex architecture and physiology of the neurovascular unit (NVU). On the other hand, studies in vivo12,13 provide detailed quantitative information on transport rates across the BBB but do not provide insights into the intracellular mechanisms of transport. Therefore, investigating the cellular and intracellular components of the NVU in vivo and ex vivo remains very challenging14. Only a limited number of techniques are amenable to analyze subcellular structures within cells of the NVU. Most studies use electron microscopy but this technique is limited by the complex protocols required for proper tissue preparation and sample handling. Therefore, we established a methodology based on high resolution confocal microscopy that would facilitate the processing of brain samples, the analysis, and the quantification of subcellular compartments within cells of the NVU.
Here, we describe a protocol which utilizes mouse brain free-floating sections to perform quantitative imaging of the BBB and NVU at the cellular and subcellular levels. We tested and validated a number of antibodies to image and reconstruct the NVU in three dimensions. Furthermore, this protocol allows imaging at the maximal optical diffraction-limited resolution of organelles within brain capillaries. Together with image analysis, this protocol can be used to investigate the intracellular transport of macromolecules across the BBB under different experimental conditions, for example in mouse disease models of neurodegeneration.

<table style="border-collapse:collapse;width:665pt" width="886">
	<colgroup>
		<col style="width:223pt" width="297" />
		<col style="width:98pt" width="130" />
		<col style="width:93pt" width="124" />
		<col style="width:251pt" width="335" />
	</colgroup>
	<tbody>
		<tr height="105" style="height:78.75pt">
			<td class="xl22" height="105" style="width:223pt;height:78.75pt" width="297">Rat monoclonal antibody clone ER-MP12 against CD31/PECAM</td>
			<td class="xl18" style="width:98pt" width="130">Novus Biologicals</td>
			<td class="xl18" style="width:93pt" width="124">MCA2388</td>
			<td class="xl18" style="width:251pt" width="335">Labels Brain Endothelial Cells 
			Use at dilution 1:100 
			detect with donkey polyclonal anti-rat IgG (H+L) coupled with suitable AlexaFluor dye, used at dilution 1:400</td>
		</tr>
		<tr height="105" style="height:78.75pt">
			<td class="xl22" height="105" style="width:223pt;height:78.75pt" width="297">Rat monoclonal antibody against Podocalyxin</td>
			<td class="xl18" style="width:98pt" width="130">R&#38;D Systems</td>
			<td class="xl18" style="width:93pt" width="124">MAB1556</td>
			<td class="xl18" style="width:251pt" width="335">Labels Lumen of capillaries 
			Use at dilution 1:100 
			detect with donkey polyclonal anti-rat IgG (H+L) coupled with suitable AlexaFluor dye, used at dilution 1:400</td>
		</tr>
		<tr height="105" style="height:78.75pt">
			<td class="xl22" height="105" style="width:223pt;height:78.75pt" width="297">Rabbit polyclonal antibody against CollagenIV</td>
			<td class="xl18" style="width:98pt" width="130">Biotrend</td>
			<td class="xl18" style="width:93pt" width="124">BT21-5014-70</td>
			<td class="xl18" style="width:251pt" width="335">Labels Basement membrane of capillaries 
			Use at dilution 1:100 
			detect with donkey polyclonal anti-rabbit IgG (H+L) coupled with suitable AlexaFluor dye, used at dilution 1:400</td>
		</tr>
		<tr height="105" style="height:78.75pt">
			<td class="xl22" height="105" style="width:223pt;height:78.75pt" width="297">Goat polyclonal antibody against CD13</td>
			<td class="xl18" style="width:98pt" width="130">R&#38;D Systems</td>
			<td class="xl18" style="width:93pt" width="124">AF2335</td>
			<td class="xl18" style="width:251pt" width="335">Labels pericytes 
			Use at dilution 1:100 
			detect with donkey polyclonal anti-goat IgG (H+L) coupled with suitable AlexaFluor dye, used at dilution 1:400</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl22" height="42" style="width:223pt;height:31.5pt" width="297">Mouse monoclonal antibody clone G-A-5 against GFAP coupled to Cy3</td>
			<td class="xl18" style="width:98pt" width="130">Abcam</td>
			<td class="xl18" style="width:93pt" width="124">ab49874</td>
			<td class="xl18" style="width:251pt" width="335">Labels Astrocytes 
			Use at dilution 1:100</td>
		</tr>
		<tr height="105" style="height:78.75pt">
			<td class="xl22" height="105" style="width:223pt;height:78.75pt" width="297">Rabbit polyclonal antibody against Iba-1</td>
			<td class="xl18" style="width:98pt" width="130">Wako</td>
			<td class="xl18" style="width:93pt" width="124">019-19741</td>
			<td class="xl18" style="width:251pt" width="335">Labels Microglia 
			Use at dilution 1:100 
			detect with donkey polyclonal anti-rat IgG (H+L) coupled with suitable AlexaFluor dye, used at dilution 1:400</td>
		</tr>
		<tr height="105" style="height:78.75pt">
			<td class="xl22" height="105" style="width:223pt;height:78.75pt" width="297">Rat monoclonal antibody ABL93 gainst LAMP2</td>
			<td class="xl18" style="width:98pt" width="130">Fitzgerald</td>
			<td class="xl18" style="width:93pt" width="124">10R-CD107BBMSP</td>
			<td class="xl18" style="width:251pt" width="335">Labels Lysosomes 
			Use at dilution 1:100 
			detect with donkey polyclonal anti-rat IgG (H+L) coupled with suitable AlexaFluor dye, used at dilution 1:400</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl23" height="42" style="width:223pt;height:31.5pt" width="297">donkey polyclonal antibody against mouse IgG (H+L) AlexaFluor594</td>
			<td class="xl18" style="width:98pt" width="130">LifeTechnologies</td>
			<td class="xl18" style="width:93pt" width="124">A21203</td>
			<td class="xl21">Use at dilution 1:400</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">donkey polyclonal antibody against mouse IgG (H+L) AlexaFluor488</td>
			<td class="xl18" style="width:98pt" width="130">LifeTechnologies</td>
			<td class="xl18" style="width:93pt" width="124">A21202</td>
			<td class="xl21">Use at dilution 1:400</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">goat polyclonal antibody against mouse IgG (H+L) AlexaFluor555</td>
			<td class="xl18" style="width:98pt" width="130">LifeTechnologies</td>
			<td class="xl18" style="width:93pt" width="124">A21422</td>
			<td class="xl21">Use at dilution 1:400</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">Filter paper</td>
			<td class="xl18" style="width:98pt" width="130">Sigma-Aldrich</td>
			<td class="xl18" style="width:93pt" width="124">WHA10334347</td>
			<td class="xl18" style="width:251pt" width="335">Whatman prepleated qualitative filter paper 
			Grade 0858 1/2, grained</td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl18" height="21" style="width:223pt;height:15.75pt" width="297">Cyanoacrylate glue</td>
			<td class="xl18" style="width:98pt" width="130">Roth Carl</td>
			<td align="right" class="xl18" style="width:93pt" width="124">258.1</td>
			<td class="xl18" style="width:251pt" width="335">Roti Coll 1</td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl18" height="21" style="width:223pt;height:15.75pt" width="297">Fluorescent Mounting medium</td>
			<td class="xl18" style="width:98pt" width="130">Dako</td>
			<td class="xl18" style="width:93pt" width="124">S3023</td>
			<td class="xl18" style="width:251pt" width="335">Dako fluorescent mounting medium</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">Adult mice</td>
			<td class="xl18" style="width:98pt" width="130">The Jackson Laboratory</td>
			<td class="xl18" style="width:93pt" width="124">000664</td>
			<td class="xl18" style="width:251pt" width="335">C57BL/6J male or female mice 
			between 9 and 19 months of age</td>
		</tr>
		<tr height="21" style="height:15.75pt">
			<td class="xl18" height="21" style="width:223pt;height:15.75pt" width="297">Vibratome</td>
			<td class="xl18" style="width:98pt" width="130">Leica Biosystems</td>
			<td align="right" class="xl18" style="width:93pt" width="124">14047235612</td>
			<td class="xl21">Leica VT100S vibrating blade microtome</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">Laser Scanning Confocal microscope</td>
			<td class="xl18" style="width:98pt" width="130">Leica Microsystems</td>
			<td class="xl18" style="width:93pt" width="124">NA</td>
			<td class="xl18" style="width:251pt" width="335">Leica TCS SP8 X with HyD detectors 
			and White light laser</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">Image processing software</td>
			<td class="xl18" style="width:98pt" width="130">Leica Microsystems</td>
			<td class="xl18" style="width:93pt" width="124">NA</td>
			<td class="xl21">Leica Application Suite AF version 3.1.0 build 8587</td>
		</tr>
		<tr height="42" style="height:31.5pt">
			<td class="xl18" height="42" style="width:223pt;height:31.5pt" width="297">Image analysis software</td>
			<td class="xl18" style="width:98pt" width="130">Bitplane scientific software</td>
			<td class="xl18" style="width:93pt" width="124">NA</td>
			<td class="xl21">Imaris version 7.6.5 build 31770 for x64</td>
		</tr>
		<tr height="99" style="height:74.25pt">
			<td class="xl18" height="99" style="width:223pt;height:74.25pt" width="297">Fluorescence SpectraViewer</td>
			<td class="xl18" style="width:98pt" width="130">ThermoFisher Scientific</td>
			<td class="xl18" style="width:93pt" width="124">NA</td>
			<td class="xl25" style="width:251pt" width="335">https://www.thermofisher.com/ch/en/home/life-science 
			/cell-analysis/labeling-chemistry/fluorescence-spectraviewer.html</td>
		</tr>
	</tbody>
</table>

high-resolution confocal imaging of the blood-brain barrier: imaging, 3d reconstruction, and quantification of transcytosis

The blood-brain barrier (BBB) is a dynamic multicellular interface that regulates the transport of molecules between the circulation and the brain. Transcytosis across the BBB regulates the delivery of hormones, metabolites, and therapeutic antibodies to the brain parenchyma. Here, we present a protocol that combines immunofluorescence of free-floating sections with laser scanning confocal microscopy and image analysis to visualize subcellular organelles within endothelial cells at the BBB. Combining this data-set with 3D image analysis software allows for the semi-automated segmentation and quantification of capillary volume and surface area, as well as the number and intensity of intracellular organelles at the BBB. The detection of mouse endogenous immunoglobulin (IgG) within intracellular vesicles and their quantification at the BBB is used to illustrate the method. This protocol can potentially be applied to the investigation of the mechanisms controlling BBB transcytosis of different molecules in vivo.

As representative examples of images obtained from the protocol described here, mouse brain sections were stained with antibodies recognizing different components of the NVU including the basement membrane, astrocytes, pericytes, and endothelial cells (see Table of Materials for specific antibodies used) (Figure 1A, D, and E). At this resolution it is possible to distinguish the individual astrocytic processes and end-feet that are in direct contact with capillaries.
To highlight the suitability of this protocol for detecting intracellular structures, brain sections from animals peripherally injected with the human anti-Tau mAb86 antibody16 were stained with a fluorescently labelled anti-human antibody (Figure 1B). mAb86 is known to specifically target neurons expressing a pathological form of Tau16. Using the protocol described herein, mAb86 was detected with diffraction-limited resolution within individual vesicular structures within neurons (Figure 1B-C). In addition, endogenous mouse IgG was detected in intracellular structures within endothelial cells but not in pericytes (Figure 1D-E and Figure 2).
The acquisition of high-resolution confocal z-stacks of the brain vasculature allows for three-dimensional segmentation of capillaries and intracellular vesicles at the BBB. Figure 2 shows an example of the process of rendering and segmenting a capillary labelled with CollagenIV and mouse IgG-positive intracellular vesicles. By quantifying a full dataset of segmented images, for example by measuring the number of vesicles per capillary volume, it is possible to study changes in intracellular transport processes under different conditions. Figure 3B-C shows the differences in mIgG vesicle number and fluorescence intensity corresponding to mIgG at the brain parenchyma, respectively, upon pericyte depletion in the pdgf-bret/ret&#160;&#160;mouse model as previously reported17. The same approach was also recently used to analyze changes in intracellular transport at the BBB between different brain regions18.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56407/56407fig1.jpg" /> 
Figure 1: Labelling of multiple cell types and subcellular structures of the neurovascular unit. Representative images of the neurovascular unit (A and D) and intracellular vesicles contained within neurons (B) or endothelial cells (E) obtained with this protocol. The maximum intensity projection image in A (top) shows the distribution of GFAP-positive astrocytes (red) surrounding capillaries labelled by CollagenIV (green). Arrows point to individual astrocytic processes. Scale bar = 20 &#181;m. At this resolution, the individual astrocyte processes and end-feet are clearly visible, as shown in the zoomed image of the boxed region (bottom). Arrowheads point to astrocytic end-feet. Scale bar = 10 &#181;m. The image in B shows the accumulation of a peripherally-injected antibody, mAb86 (green), within a hippocampal neuron. Arrowheads point to individual mAb86-positive vesicles. Scale bar = 10 &#181;m. The graph in C shows the line profile intensity of a single vesicle. The vesicle size was estimated from the full width at half maximum of a Gaussian fit (black solid line) of the intensity curve (green line and circles). The images in D show a three-dimensional reconstruction of an endothelial cell (green) surrounded by a pericyte (red) within the basal lamina (CollagenIV, grey). The lower panels show the individual fluorescence channels. Scale bar = 10 &#181;m. The images in E show the localization of mIgG (red) in intracellular vesicles within endothelial cells (left panel, CD31 in green) but not in pericytes (right panel, CD13 in green). In all images, DAPI stained nuclei are shown in blue. Scale bar = 5 &#181;m. Panels D&#160;and E&#160;have been modified from reference17. <a href="https://cloudflare.jove.com/files/ftp_upload/56407/56407fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56407/56407fig2.jpg" /> 
Figure 2: Three-dimensional rendering of capillaries and intracellular vesicles at the blood-brain barrier. With the protocol described, high-resolution confocal images of CollagenIV-positive capillaries (green) and mouse IgG intracellular vesicles (red) were acquired (A). The left panel shows a single optical section with cross-sections. The arrows point to individual mIgG-positive vesicles within brain endothelial cells. The panel on the right shows the 3D reconstruction of the full z-stack using image processing software (see Table of Materials). The capillary volume (B) and individual vesicles (C) were rendered in three dimensions and quantified using image processing software (see Table of Materials). In all images, DAPI stained nuclei are shown in blue. Scale bars = 5 &#181;m. <a href="https://cloudflare.jove.com/files/ftp_upload/56407/56407fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56407/56407fig3.jpg" /> 
Figure 3: Quantification of mIgG intracellular localization at the BBB. Representative images showing (A) three-dimensional reconstructions of capillaries (labelled with collagenIV, green) and the distribution of mIgG (red) in C57BL/6 mice and in pdgf-bret/ret pericyte depleted mice previously described in19. Scale bars = 10 &#181;m. The images in B show the segmentation of intracellular vesicles within the CollagenIV mask. The graph in B shows the quantification and comparison of mIgG vesicle number per volume of capillary. Each point represents measurements from individual capillary segments. The solid line shows the mean and the error bars represent the standard deviation of the data. The images in C show the&#160;mIgG fluorescence signal outside the CollagenIV mask. Similarly, the graph in C shows the quantification and comparison of mIgG fluorescence intensity in the brain parenchyma between C57BL/6 mice and pdgf-bret/ret pericyte depleted mice. Fluorescence intensity units were normalized by the average mIgG parenchyma intensity measured in all C57BL/6 mice. This figure has been modified from reference17.&#160;<a href="https://cloudflare.jove.com/files/ftp_upload/56407/56407fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about High-resolution Confocal Imaging of the Blood-brain Barrier: Imaging, 3D Reconstruction, and Quantification of Transcytosis at JoVE.com

High-resolution Confocal Imaging of the Blood-brain Barrier: Imaging, 3D Reconstruction, and Quantification of Transcytosis

Hochauflösende konfokale Bildgebung der Blut - Hirn-Schranke: Bildgebung, 3D-Rekonstruktion und Quantifizierung der Transcytosis

Here we present a microscopy-based protocol for high-resolution imaging and a three-dimensional reconstruction of the mouse neurovascular unit and blood-brain barrier using brain free-floating sections. This method allows for the visualization, analysis, and quantification of intracellular organelles at the BBB.

The blood-brain barrier (BBB) is a dynamic multicellular interface that regulates the transport of molecules between the circulation and the brain. ...

The overall goal of this method is to provide a microscopy-based protocol for high-resolution imaging and 3-dimensional reconstruction of the mouse blood-brain barrier.It combines immunofluorescence of free-floating sections with confocal microscopy to analyze subcellular organelles within the brain endothelial cells.This method add learns the preparation of brain free-floating sections, immunofluorescence staining, image acquisition and analysis parameters for high-resolution microscopy of the blood-brain barrier.The main advantage of the technique is that it allows for the quantification of subcellular organelles within cells of the neurovascular unit.Demonstrating the procedure will be Roberto Villase

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11.6K Aufrufe.  Roche Innovation Center Basel. The overall goal of this method is to provide a microscopy-based protocol for high-resolution imaging and 3-dimensional reconstruction of the mouse blood-brain barrier.It combines immunofluorescence of free-floating sections with confocal microscopy to analyze subcellular organelles within the brain endothelial cells.This method add learns the preparation of brain free-floating sections, immunofluorescence staining, image acquisition and analysis parameters for high-resolution microscopy of t...

Serie: High-resolution Confocal Imaging of the Blood-brain Barrier: Imaging, 3D Reconstruction, and Quantification of Transcytosis

An Organotypic Slice Assay for High-Resolution Time-Lapse Imaging of Neuronal Migration in the Postnatal Brain

Neurogenesis in the postnatal brain depends on maintenance of three biological events: proliferation of progenitor cells, migration of neuroblasts, as well as differentiation and integration of new neurons into existing neural circuits. For postnatal neurogenesis in the olfactory bulbs, these events are segregated within three anatomically distinct domains: proliferation largely occurs in the subependymal zone (SEZ) of the lateral ventricles, migrating neuroblasts traverse through the rostral migratory stream (RMS), and new neurons differentiate and integrate within the olfactory bulbs (OB). The three domains serve as ideal platforms to study the cellular, molecular, and physiological mechanisms that regulate each of the biological events distinctly. This paper describes an organotypic slice assay optimized for postnatal brain tissue, in which the extracellular conditions closely mimic the in vivo environment for migrating neuroblasts. We show that our assay provides for uniform, oriented, and speedy movement of neuroblasts within the RMS. This assay will be highly suitable for the study of cell autonomous and non-autonomous regulation of neuronal migration by utilizing cross-transplantation approaches from mice on different genetic backgrounds.

This protocol describes an organotypic slice assay optimized for the postnatal brain and high-resolution time-lapse imaging of neuroblast migration in the rostral migratory stream.

Ein organotypischen Assay für High-Resolution Time-Lapse Imaging neuronaler Migration in der postnatalen Gehirn

Neurogenesis in the postnatal brain depends on maintenance of three biological events: proliferation of progenitor cells, migration of neuroblasts, as ...

Forschung

Neurowissenschaften

A Rapid Approach to High-Resolution Fluorescence Imaging in Semi-Thick Brain Slices

A fundamental goal to both basic and clinical neuroscience is to better understand the identities, molecular makeup, and patterns of connectivity that are characteristic to neurons in both normal and diseased brain. Towards this, a great deal of effort has been placed on building high-resolution neuroanatomical maps1-3. With the expansion of molecular genetics and advances in light microscopy has come the ability to query not only neuronal morphologies, but also the molecular and cellular makeup of individual neurons and their associated networks4. Major advances in the ability to mark and manipulate neurons through transgenic and gene targeting technologies in the rodent now allow investigators to 'program' neuronal subsets at will5-6. Arguably, one of the most influential contributions to contemporary neuroscience has been the discovery and cloning of genes encoding fluorescent proteins (FPs) in marine invertebrates7-8, alongside their subsequent engineering to yield an ever-expanding toolbox of vital reporters9. Exploiting cell type-specific promoter activity to drive targeted FP expression in discrete neuronal populations now affords neuroanatomical investigation with genetic precision.
Engineering FP expression in neurons has vastly improved our understanding of brain structure and function. However, imaging individual neurons and their associated networks in deep brain tissues, or in three dimensions, has remained a challenge. Due to high lipid content, nervous tissue is rather opaque and exhibits auto fluorescence. These inherent biophysical properties make it difficult to visualize and image fluorescently labelled neurons at high resolution using standard epifluorescent or confocal microscopy beyond depths of tens of microns. To circumvent this challenge investigators often employ serial thin-section imaging and reconstruction methods10, or 2-photon laser scanning microscopy11. Current drawbacks to these approaches are the associated labor-intensive tissue preparation, or cost-prohibitive instrumentation respectively.
Here, we present a relatively rapid and simple method to visualize fluorescently labelled cells in fixed semi-thick mouse brain slices by optical clearing and imaging. In the attached protocol we describe the methods of: 1) fixing brain tissue in situ via intracardial perfusion, 2) dissection and removal of whole brain, 3) stationary brain embedding in agarose, 4) precision semi-thick slice preparation using new vibratome instrumentation, 5) clearing brain tissue through a glycerol gradient, and 6) mounting on glass slides for light microscopy and z-stack reconstruction (Figure 1).
For preparing brain slices we implemented a relatively new piece of instrumentation called the 'Compresstome' VF-200 (http://www.precisionary.com/products_vf200.html). This instrument is a semi-automated microtome equipped with a motorized advance and blade vibration system with features similar in function to other vibratomes. Unlike other vibratomes, the tissue to be sliced is mounted in an agarose plug within a stainless steel cylinder. The tissue is extruded at desired thicknesses from the cylinder, and cut by the forward advancing vibrating blade. The agarose plug/cylinder system allows for reproducible tissue mounting, alignment, and precision cutting. In our hands, the 'Compresstome' yields high quality tissue slices for electrophysiology, immunohistochemistry, and direct fixed-tissue mounting and imaging. Combined with optical clearing, here we demonstrate the preparation of semi-thick fixed brain slices for high-resolution fluorescent imaging.

Here we describe a rapid and simple method to image fluorescently labeled cells in semi-thick brain slices. By fixing, slicing, and optically clearing brain tissue we describe how standard epifluorescent or confocal imaging can be used to visualize individual cells and neuronal networks within intact nervous tissue.

Eine schnelle Annäherung an High-Resolution Fluoreszenz-Imaging in Semi-Thick Hirnschnitten

A fundamental goal to both basic and clinical neuroscience is to better understand the identities, molecular makeup, and patterns of connectivity that are ...

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1. Since, T2* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE ~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4.
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.

This article describes techniques to perform high-resolution functional magnetic resonance imaging with 1.2 mm sampling in human midbrain and subcortical structures using a 3T scanner. Use of these techniques to resolve topographic maps of visual stimulation in the human superior colliculus (SC) is given as an example.

Hochauflösende Functional Magnetic Resonance Imaging Methods for Human Mittelhirn

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon ...

High-resolution Live Imaging of Cell Behavior in the Developing Neuroepithelium

The embryonic spinal cord consists of cycling neural progenitor cells that give rise to a large percentage of the neuronal and glial cells of the central nervous system (CNS). Although much is known about the molecular mechanisms that pattern the spinal cord and elicit neuronal differentiation1, 2, we lack a deep understanding of these early events at the level of cell behavior. It is thus critical to study the behavior of neural progenitors in real time as they undergo neurogenesis.
In the past, real-time imaging of early embryonic tissue has been limited by cell/tissue viability in culture as well as the phototoxic effects of fluorescent imaging. Here we present a novel assay for imaging such tissue for long periods of time, utilizing a novel ex vivo slice culture protocol and wide-field fluorescence microscopy (Fig. 1). This approach achieves long-term time-lapse monitoring of chick embryonic spinal cord progenitor cells with high spatial and temporal resolution.
This assay may be modified to image a range of embryonic tissues3, 4 In addition to the observation of cellular and sub-cellular behaviors, the development of novel and highly sensitive reporters for gene activity (for example, Notch signaling5) makes this assay a powerful tool with which to understand how signaling regulates cell behavior during embryonic development.

Imaging embryonic tissue in real-time is challenging over long periods of time. Here we present an assay for monitoring cellular and sub-cellular changes in chick spinal cord for long periods with high spatial and temporal resolution. This technique can be adapted for other regions of the nervous system and developing embryo.

Hochauflösende Live-Bildgebung von Zell-Verhalten in der Entwicklung von Neuroepithel

The embryonic spinal cord consists of cycling neural progenitor cells that give rise to a large percentage of the neuronal and glial cells of the central ...

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has been heavily studied. While many imaging studies treat the hippocampus as a single unitary neuroanatomical structure, it is, in fact, composed of several subfields that have a complex three-dimensional geometry. As such, it is known that these subfields perform specialized functions and are differentially affected through the course of different disease states. Magnetic resonance (MR) imaging can be used as a powerful tool to interrogate the morphology of the hippocampus and its subfields. Many groups use advanced imaging software and hardware (&#62;3T) to image the subfields; however this type of technology may not be readily available in most research and clinical imaging centers. To address this need, this manuscript provides a detailed step-by-step protocol for segmenting the full anterior-posterior length of the hippocampus and its subfields: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus (DG), strata radiatum/lacunosum/moleculare (SR/SL/SM), and subiculum. This protocol has been applied to five subjects (3F, 2M; age 29-57, avg. 37). Protocol reliability is assessed by resegmenting either the right or left hippocampus of each subject and computing the overlap using the Dice&#39;s kappa metric. Mean Dice&#39;s kappa (range) across the five subjects are: whole hippocampus, 0.91 (0.90-0.92); CA1, 0.78 (0.77-0.79); CA2/CA3, 0.64 (0.56-0.73); CA4/dentate gyrus, 0.83 (0.81-0.85); strata radiatum/lacunosum/moleculare, 0.71 (0.68-0.73); and subiculum 0.75 (0.72-0.78). The segmentation protocol presented here provides other laboratories with a reliable method to study the hippocampus and hippocampal subfields in vivo using commonly available MR tools.

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging

The goal of this manuscript is to study the hippocampus and hippocampal subfields using MRI. The manuscript describes a protocol for segmenting the hippocampus and five hippocampal substructures: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, strata radiatum/lacunosum/moleculare, and subiculum.

Hohe Auflösung<em&gt; In-vivo-</em&gt; Manuelle Segmentierung Protokoll für Menschen Hippocampus Teilfelder Verwenden von 3T Kernspintomographie

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has ...

High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

The focus of this study was to test the resolution limits of structural MRI of a postmortem brain compared to living human brains. The resolution of structural MRI in vivo is ultimately limited by physiological noise, including pulsation, respiration and head movement. Although imaging hardware continues to improve, it is still difficult to resolve structures on the millimeter scale. For example, the primary visual sensory pathways synapse at the lateral geniculate nucleus (LGN), a visual relay and control nucleus in the thalamus that normally is organized into six interleaved monocular layers. Neuroimaging studies have not been able to reliably distinguish these layers due their small size that are less than 1 mm thick.
The resolving limit of structural MRI, in a postmortem brain was tested using multiple images averaged over a long duration (~24 h). The purpose was to test whether it was possible to resolve the individual layers of the LGN in the absence of physiological noise. A proton density (PD)1 weighted pulse sequence was used with varying resolution and other parameters to determine the minimum number of images necessary to be registered and averaged to reliably distinguish the LGN and other subcortical regions. The results were also compared to images acquired in living human brains. In vivo subjects were scanned in order to determine the additional effects of physiological noise on the minimum number of PD scans needed to differentiate subcortical structures, useful in clinical applications.

High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem

Here we present a protocol to determine the minimum number images that needed to be registered and averaged to resolve subcortical structures and test whether the individual layers of the LGN could be resolved in the absence of physiological noise.

Hochauflösende Strukturkernspintomographie des menschlichen Subcortex<I&gt; In-vivo-</I&gt; Und Postmortem

The focus of this study was to test the resolution limits of structural MRI of a postmortem brain compared to living human brains. The resolution of ...

High-Resolution Quantitative Immunogold Analysis of Membrane Receptors at Retinal Ribbon Synapses

Retinal ganglion cells (RGCs) receive excitatory glutamatergic input from bipolar cells. Synaptic excitation of RGCs is mediated postsynaptically by NMDA receptors (NMDARs) and AMPA receptors (AMPARs). Physiological data have indicated that glutamate receptors at RGCs are expressed not only in postsynaptic but also in perisynaptic or extrasynaptic membrane compartments. However, precise anatomical locations for glutamate receptors at RGC synapses have not been determined. Although a high-resolution quantitative analysis of glutamate receptors at central synapses is widely employed, this approach has had only limited success in the retina. We developed a postembedding immunogold method for analysis of membrane receptors, making it possible to estimate the number, density and variability of these receptors at retinal ribbon synapses. Here we describe the tools, reagents, and the practical steps that are needed for: 1) successful preparation of retinal fixation, 2) freeze-substitution, 3) postembedding immunogold electron microscope (EM) immunocytochemistry and, 4) quantitative visualization of glutamate receptors at ribbon synapses.

The postembedding immunogold method is one of the most effective ways to provide high-resolution analyses of the subcellular localization of specific molecules. Here we describe a protocol to quantitatively analyze glutamate receptors at retinal ribbon synapses.

Hochauflösende Quantitative Immungold-Analyse von Membranrezeptoren auf der Netzhaut Ribbon Synapsen

Retinal ganglion cells (RGCs) receive excitatory glutamatergic input from bipolar cells. Synaptic excitation of RGCs is mediated postsynaptically by NMDA ...

Using a Microfluidics Device for Mechanical Stimulation and High Resolution Imaging of C. elegans

One central goal of mechanobiology is to understand the reciprocal effect of mechanical stress on proteins and cells. Despite its importance, the influence of mechanical stress on cellular function is still poorly understood. In part, this knowledge gap exists because few tools enable simultaneous deformation of tissue and cells, imaging of cellular activity in live animals, and efficient restriction of motility in otherwise highly mobile model organisms, such as the nematode Caenorhabditis elegans. The small size of C. elegans makes them an excellent match to microfluidics-based research devices, and solutions for immobilization have been presented using microfluidic devices. Although these devices allow for high-resolution imaging, the animal is fully encased in polydimethylsiloxane (PDMS) and glass, limiting physical access for delivery of mechanical force or electrophysiological recordings. Recently, we created a device that integrates pneumatic actuators with a trapping design that is compatible with high-resolution fluorescence microscopy. The actuation channel is separated from the worm-trapping channel by a thin PDMS diaphragm. This diaphragm is deflected into the side of a worm by applying pressure from an external source. The device can target individual mechanosensitive neurons. The activation of these neurons is imaged at high-resolution with genetically-encoded calcium indicators. This article presents the general method using C. elegans strains expressing calcium-sensitive activity indicator (GCaMP6s) in their touch receptor neurons (TRNs). The method, however, is not limited to TRNs nor to calcium sensors as a probe, but can be expanded to other mechanically-sensitive cells or sensors.

Using a Microfluidics Device for Mechanical Stimulation and High Resolution Imaging of C. elegans

New tools for mechanobiology research are needed to understand how mechanical stress activates biochemical pathways and elicits biological responses. Here, we showcase a new method for selective mechanical stimulation of immobilized animals with a microfluidic trap allowing high-resolution imaging of cellular responses.

Verwendung von einem Mikrofluidik-Gerät für mechanische Stimulation und High Resolution Imaging von C. elegans

One central goal of mechanobiology is to understand the reciprocal effect of mechanical stress on proteins and cells. Despite its importance, the ...

High-resolution Volume Imaging of Neurons by the Use of Fluorescence eXclusion Method and Dedicated Microfluidic Devices

Volume is an important parameter regarding physiological and pathological characteristics of neurons at different time scales. Neurons are quite unique cells regarding their extended ramified morphologies and consequently raise several methodological challenges for volume measurement. In the particular case of in vitro neuronal growth, the chosen methodology should include sub-micrometric axial resolution combined with full-field observation on time scales from minutes to hours or days. Unlike other methods like cell shape reconstruction using confocal imaging, electrically-based measurements or Atomic Force Microscopy, the recently developed Fluorescence eXclusion method (FXm) has the potential to fulfill these challenges. However, although being simple in its principle, implementation of a high-resolution FXm for neurons requires multiple adjustments and a dedicated methodology. We present here a method based on the combination of fluorescence exclusion, low-roughness multi-compartments microfluidic devices, and finally micropatterning to achieve in vitro measurements of local neuronal volume. The high resolution provided by the device allowed us to measure the local volume of neuronal processes (neurites) and the volume of some specific structures involved in neuronal growth, such as growth cones (GCs).

Volume is an important parameter regarding physiological and pathological characteristics of cells. We describe a fluorescent exclusion method allowing full-field measurement of in vitro neuronal volume with sub-micrometric axial resolution required for the analysis of neurites and dynamic structures implied in neuronal growth.

Hochauflösende Volume Imaging von Neuronen durch den Einsatz von Fluoreszenz-Ausschluss Methode und mikrofluidischen Geräten gewidmet

Volume is an important parameter regarding physiological and pathological characteristics of neurons at different time scales. Neurons are quite unique ...

High-Resolution 3D Imaging of Rabies Virus Infection in Solvent-Cleared Brain Tissue

The visualization of infection processes in tissues and organs by immunolabeling is a key method in modern infection biology. The ability to observe and study the distribution, tropism, and abundance of pathogens inside of organ tissues provides pivotal data on disease development and progression. Using conventional microscopy methods, immunolabeling is mostly restricted to thin sections obtained from paraffin-embedded or frozen samples. However, the limited 2D image plane of these thin sections may lead to the loss of crucial information on the complex structure of an infected organ and the cellular context of the infection. Modern multicolor, immunostaining-compatible tissue clearing techniques now provide a relatively fast and inexpensive way to study high-volume 3D image stacks of virus-infected organ tissue. By exposing the tissue to organic solvents, it becomes optically transparent. This matches the sample&#8217;s refractive indices and eventually leads to a significant reduction of light scattering. Thus, in combination with long free working distance objectives, large tissue sections up to 1 mm in size can be imaged by conventional confocal laser scanning microscopy (CLSM) at high resolution. Here, we describe a protocol to apply deep-tissue imaging after tissue clearing to visualize rabies virus distribution in infected brains in order to study topics like virus pathogenesis, spread, tropism, and neuroinvasion.

Novel, immunostaining-compatible tissue clearing techniques like the ultimate 3D imaging of solvent-cleared organs allow the 3D visualization of rabies virus brain infection and its complex cellular environment. Thick, antibody-labeled brain tissue slices are made optically transparent to increase imaging depth and to enable 3D analysis by confocal laser scanning microscopy.

Hochauflösende 3D-Bildgebung der Tollwut-Virusinfektion im lösungsmittelfreien Hirngewebe

The visualization of infection processes in tissues and organs by immunolabeling is a key method in modern infection biology. The ability to observe and ...